tf_fwd = muscat.computeconvolution(muscat.TF_ATF,
myfac=myfac,
myabsnorm=myabsnorm)
#%%
''' Compute a first guess based on the experimental phase '''
init_guess = np.ones(matlab_val.shape) # np.angle(matlab_val)##
#init_guess = init_guess-np.min(init_guess)
init_guess = dn * init_guess / np.max(
init_guess) + muscat.nEmbb #*dn+1j*.01*np.ones(init_guess.shape)
if (0):
mydiameter = 5
obj = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=muscat.dx,
obj_type='sphere',
diameter=mydiameter,
dn=dn) #)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=muscat.dx,
obj_type='sphere',
diameter=mydiameter,
dn=.01)
init_guess = muscat.nEmbb + obj + 1j * obj_absorption * 0
#%%
'''# Estimate the Phase difference between Measurement and Simulation'''
# This is actually a crucial step and needs to be used with care. We don't want any phase wrappings !
'''Numpy to Tensorflow'''
np_meas = matlab_val
#np_mean = 1#np.mean(np_meas)
#np_meas = np_meas/np_mean
#muscat.Nx = 64; muscat.Ny = 64; muscat.Nz = 70
#muscat.dz = muscat.lambda0/4
#muscat.Nz = 36
mymatfile = '/Users/bene/Dropbox/Dokumente/Promotion/PROJECTS/BOSTON/MUSCAT/MATLAB/MuScat/mtfs.mat'
matatf = data.import_realdata_h5(filename = mymatfile, matname='myatf', is_complex=True)
matasf = data.import_realdata_h5(filename = mymatfile, matname='myasf', is_complex=True)
''' Adjust some parameters to fit it in the memory '''
muscat.mysize = (muscat.Nz,muscat.Nx,muscat.Ny) # ordering is (Nillu, Nz, Nx, Ny)
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
mydiameter = 5
if(1):
obj_real= tf_go.generateObject(mysize=muscat.mysize, obj_dim=1, obj_type ='sphere', diameter = mydiameter, dn = dn, nEmbb = muscat.nEmbb)#)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize, obj_dim=1, obj_type ='sphere', diameter = mydiameter, dn = .0, nEmbb = 0.01)
elif(1):
obj_real = tf_go.generateObject(mysize=muscat.mysize, obj_dim=1, obj_type ='hollowsphere', diameter = mydiameter, dn = dn, nEmbb = muscat.nEmbb)#)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='sphere', diameter = mydiameter, dn = .0)
elif(0):
obj_real= tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='twosphere', diameter = mydiameter/8, dn = dn)#)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='twosphere', diameter = mydiameter/8, dn = .0)
elif(0):
obj_real= tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='foursphere', diameter = mydiameter/8, dn = dn)#)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='foursphere', diameter = mydiameter/8, dn = .00)
elif(0):
obj_real= tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='eightsphere', diameter = mydiameter/8, dn = dn)#)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='eightsphere', diameter = mydiameter/8, dn = .01)
elif(0):
# load a neuron
muscat.shiftIcX = experiments.shiftIcX
muscat.NAc = experiments.NAc
''' Adjust some parameters to fit it in the memory '''
muscat.mysize = (muscat.Nz, muscat.Nx, muscat.Ny
) # ordering is (Nillu, Nz, Nx, Ny)
# introduce zernike factors here
muscat.zernikefactors = experiments.zernikefactors
muscat.zernikemask = experiments.zernikemask
''' Compute a first guess based on the experimental phase '''
obj_guess = np.zeros(matlab_val.shape) + muscat.nEmbb # np.angle(matlab_val)##
import src.tf_generate_object as tf_go
mydiameter = 5
obj_guess = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=1,
obj_type='sphere',
diameter=mydiameter,
dn=.05,
nEmbb=1.33) #)dn)
n_r = obj_guess #obj.astype("float32") / np.max(obj) * NumPhot
k02 = (2 * np.pi * muscat.nEmbb / muscat.lambda0)**2
V = (k02 / (4 * np.pi)) * (n_r**2 - muscat.nEmbb**2)
''' Compute the systems model'''
# Compute the System's properties (e.g. Pupil function/Illumination Source, K-vectors, etc.)¶
muscat.computesys(obj=obj_guess, is_compute_psf='BORN', is_dampic=.02)
''' Create Model Instance'''
muscat.computemodel()
print('Start Session')
sess = tf.Session()
sess.run(tf.global_variables_initializer())
''' Create the Model'''
muscat = mus.MuScatModel(matlab_pars, is_optimization=is_optimization, is_optimization_psf = is_optimization_psf)
muscat.Nx,muscat.Ny = int(np.squeeze(matlab_pars['Nx'].value)), int(np.squeeze(matlab_pars['Ny'].value))
muscat.shiftIcY=0
muscat.shiftIcX=0
muscat.dn = dn
#muscat.NAc =.4
muscat.dz = muscat.lambda0/4
print('Attention: Changed Z-sampling!!')
''' Adjust some parameters to fit it in the memory '''
muscat.mysize = (muscat.Nz,muscat.Nx,muscat.Ny) # ordering is (Nillu, Nz, Nx, Ny)
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
obj = tf_go.generateObject(mysize=muscat.mysize, obj_dim=muscat.dx, obj_type ='sphere', diameter = , dn = muscat.dn)
# introduce zernike factors here
muscat.zernikefactors = zernikefactors
''' Compute the systems model'''
muscat.computesys(obj, is_zernike=True)
tf_fwd = muscat.computemodel()
if(is_display):
plt.subplot(131), plt.title('Ic'), plt.imshow(muscat.Ic)
plt.subplot(132), plt.title('Po'),plt.imshow(np.fft.fftshift(np.abs(muscat.Po))), plt.colorbar()
plt.subplot(133), plt.title('Po'),plt.imshow(np.fft.fftshift(np.angle(muscat.Po))), plt.colorbar(), plt.show()
muscat.Nx, muscat.Ny = int(np.squeeze(matlab_pars['Nx'].value)), int(
np.squeeze(matlab_pars['Ny'].value))
muscat.shiftIcY = shiftIcY
muscat.shiftIcX = shiftIcX
muscat.dn = dn
muscat.NAc = NAc
#muscat.lambdaM = .7
#muscat.dz = muscat.lambdaM/4
#print('Attention: Changed Z-sampling!!')
''' Adjust some parameters to fit it in the memory '''
muscat.mysize = (muscat.Nz, muscat.Nx, muscat.Ny
) # ordering is (Nillu, Nz, Nx, Ny)
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
obj = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=(muscat.dz, muscat.dx, muscat.dy),
obj_type='sphere',
diameter=1,
dn=muscat.dn)
# introduce zernike factors here
muscat.zernikefactors = zernikefactors
# Compute the System's properties (e.g. Pupil function/Illumination Source, K-vectors, etc.)¶
''' Compute the systems model'''
muscat.computesys(obj, is_zernike=True, is_padding=is_padding, dropout_prob=1)
print(muscat.Ic.shape)
# Generate Computational Graph (fwd model)
tf_fwd = muscat.computemodel()
# Define Optimizer and Cost-function
muscat.dn = dn
muscat.NAc = NAc
#muscat.dz = muscat.lambda0/2
''' Adjust some parameters to fit it in the memory '''
muscat.mysize = (muscat.Nz, muscat.Nx, muscat.Ny
) # ordering is (Nillu, Nz, Nx, Ny)
# introduce zernike factors here
muscat.zernikefactors = zernikefactors
muscat.zernikemask = zernikemask
''' Compute the systems model'''
# Compute the System's properties (e.g. Pupil function/Illumination Source, K-vectors, etc.)¶
mydiameter = 10
obj_real = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=muscat.dx,
obj_type='sphere',
diameter=mydiameter,
dn=dn,
nEmbb=muscat.nEmbb) #)dn)
obj_absorption = tf_go.generateObject(mysize=muscat.mysize,
obj_dim=muscat.dx,
obj_type='sphere',
diameter=mydiameter,
dn=.0,
nEmbb=0)
obj = obj_real + 1j * obj_absorption
muscat.computesys(obj=obj,
is_padding=is_padding,
mysubsamplingIC=mysubsamplingIC,
is_compute_psf='corr')
''' Create Model Instance'''
muscat.computemodel()
1.) Read in the parameters of the dataset '''
matlab_par_name = 'myParameter' #'./Data/DROPLETS/myParameterNew.mat';matname='myParameterNew' #'./Data/DROPLETS/myParameterNew.mat'
matlab_par_file = './Data/DROPLETS/S19_multiple/Parameter.mat'; matname='myParameter'
matlab_pars = data.import_parameters_mat(filename = matlab_par_file, matname=matlab_par_name)
''' Create a 3D Refractive Index Distributaton as a artificial sample
2.) Read in the virtual sample '''
# Fake Cheek-Cell
matlab_val_file = './Data/PHANTOM/HeLa_cell_mat_obj.mat'; matname='HeLa_cell_mat'
obj_real = data.import_realdata_h5(filename = matlab_val_file, matname=matname)
if(0):
mysize = np.array((128,128,128))
mydiameter=1
obj_real= tf_go.generateObject(mysize=mysize, obj_dim=1, obj_type ='twosphere', diameter = mydiameter, dn = .02, nEmbb = 1.33)#)dn)
#TF_obj = tf.cast(tf.complex(obj_real,obj_real*0), tf.complex64)
TF_obj = tf.cast(tf.placeholder_with_default(obj_real, obj_real.shape), tf.complex64)
# etract scattering subroi-region
mysize = obj_real.shape
mysize_sub = ((32,32,32)); mycenter = ((mysize[0]//2,mysize[1]//2,mysize[1]//2)) # Region around the nuclei
TF_obj_sub = tf_helper.extract((TF_obj-1.33)*2*np.pi, mysize_sub, mycenter)
''' Create the Model'''
muscat = mus.MuScatModel(matlab_pars, is_optimization=is_optimization)
muscat_sub = mus.MuScatModel(matlab_pars, is_optimization=is_optimization)
# some adjustments of global model
init_guess = init_guess - np.min(init_guess)
init_guess = dn * init_guess / np.max(
init_guess) #*dn+1j*.01*np.ones(init_guess.shape)
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
#for sphere5
mydiameter = 3
obj = matlab_val
squeezefac = muscat.dx / muscat.dz
obj = (
((squeezefac * tf_helper.xx(mysize=obj.shape)**2) +
(tf_helper.yy(mysize=obj.shape)**2) +
(squeezefac * tf_helper.zz(mysize=obj.shape)**2)) < (mydiameter**2)
) * dn #tf_go.generateObject(mysize=obj.shape, obj_dim=muscat.dx, obj_type ='sphere', diameter = mydiameter, dn = dn)
obj_absorption = tf_go.generateObject(mysize=obj.shape,
obj_dim=muscat.dx,
obj_type='sphere',
diameter=mydiameter,
dn=.01)
obj = obj + 1j * obj_absorption
obj = np.roll(obj, 5, 0) # z
obj = np.roll(obj, -3, 1) # y
obj = np.roll(obj, 1, 2) # x
init_guess = obj
if (False):
init_guess = matlab_val
init_guess = dn * np.angle(init_guess) - np.min(np.angle(init_guess))
init_guess = init_guess / np.max(init_guess) * dn + 1j * .01 * np.ones(
init_guess.shape)
plt.subplot(231), plt.imshow(np.real(
''' Create the Model'''
muscat = mus.MuScatModel(myparams, is_optimization=is_optimization)
# optional: assign some external paramters which are not in the simulation file
muscat.zernikefactors = experiments.zernikefactors# introduce zernike factors here
muscat.zernikemask = experiments.zernikemask # this is only important for optimization
#muscat.zernikefactors = np.array((0,0,0,0,0,0,.1,-1,0,0,-2)) # 7: ComaX, 8: ComaY, 11: Spherical Aberration
#%%
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
mydiameter = 1
objtype = 'sphere'#'cheek100' # 'sphere', 'twosphere', 'slphantom'
if(objtype == 'sphere'):
obj_real= tf_go.generateObject(mysize=myparams.mysize, obj_dim=np.array((myparams.dz, myparams.dx, myparams.dy)), obj_type ='sphere', diameter = mydiameter, dn = experiments.dn, nEmbb = myparams.nEmbb)#)dn)
obj_absorption= tf_go.generateObject(mysize=myparams.mysize, obj_dim=np.array((myparams.dz, myparams.dx, myparams.dy)), obj_type ='sphere', diameter = mydiameter, dn = .01, nEmbb = 0.)#)dn)
elif(0):
obj_real = tf_go.generateObject(mysize=myparams.mysize, obj_dim=1, obj_type ='hollowsphere', diameter = mydiameter, dn = experiments.dn, nEmbb = myparams.nEmbb)#)dn)
obj_absorption = tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='sphere', diameter = mydiameter, dn = .0)
elif(0):
obj_real= tf_go.generateObject(mysize=myparams.mysize, obj_dim=1, obj_type ='twosphere', diameter = mydiameter, dn = experiments.dn, nEmbb = myparams.nEmbb)
obj_absorption = tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='twosphere', diameter = mydiameter, dn = .0)
elif(0):
obj_real= tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='foursphere', diameter = mydiameter/8, dn = experiments.dn)#)dn)
obj_absorption = tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='foursphere', diameter = mydiameter/8, dn = .00)
elif(0):
obj_real= tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='eightsphere', diameter = mydiameter/8, dn = experiments.dn)#)dn)
obj_absorption = tf_go.generateObject(mysize=myparams.mysize, obj_dim=muscat.dx, obj_type ='eightsphere', diameter = mydiameter/8, dn = .01)
elif(0):
# load a neuron
myparams = paras.MyParameter()
myparams.loadExperiment(experiments)
myparams.print()
# reset default graph
tf.reset_default_graph()
''' Create the Model'''
muscat = mus.MuScatModel(myparams, is_optimization=is_optimization)
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
mydiameter = 1
objtype = 'sphere' # 'cheek100'#'cheek100' # 'sphere', 'twosphere', 'slphantom'
if (objtype == 'sphere'):
obj_real = tf_go.generateObject(mysize=myparams.mysize,
obj_dim=np.array((myparams.dz, myparams.dx,
myparams.dy)),
obj_type='sphere',
diameter=mydiameter,
dn=experiments.dn,
nEmbb=myparams.nEmbb) #)dn)
obj_absorption = tf_go.generateObject(mysize=myparams.mysize,
obj_dim=np.array(
(myparams.dz, myparams.dx,
myparams.dy)),
obj_type='sphere',
diameter=mydiameter,
dn=.01,
nEmbb=0.) #)dn)
elif (objtype == 'cheek100'):
# Fake Cheek-Cell
matlab_val_file = './Data/PHANTOM/HeLa_cell_mat_obj_100.mat'
matname = 'HeLa_cell_mat'
# In[ ]:
# Load Copute the systems model
#if(load_data):
# mm.loadData()
#else:
# mm.allSumAmp_mes = matlab_val
#
# ## Generate a phantom object in 3D
# In[ ]:
''' Create a 3D Refractive Index Distributaton as a artificial sample'''
obj = tf_go.generateObject(mysize=mm.mysize,
obj_dim=mm.dx,
obj_type=1,
diameter=1,
dn=mm.dn)
# ## Create computational graph
# In[ ]:
''' Assign Object (3D sample) to Class'''
mm.obj_init = tf_go.generateInitObject(obj)
''' Create computational graph'''
mm.create_graph(obj, if_xla=0)
# ## Now evaluate the result - start inference
# In[ ]:
'''Compute result'''
